Lane level traffic information is becoming increasingly more desirable by traffic service providers. Lane level traffic information may support a number of technologies including advanced navigation systems, connected vehicles and autonomous vehicles. However, the collection of accurate lane level traffic information is challenging and it remains difficult to reliably identify the location of a vehicle with the precision required to reliably place the vehicle within a respective lane of a road segment. Instead, most vehicles are located, such as by global positioning systems (GPS), in such a manner that the vehicles may be matched to a respective road segment, but not to any particular lane of the road segment.
The technique has been developed, however, to identify split lane traffic, that is, the traffic that travels along a road segment that splits or is otherwise divided into two or more downstream road segments, such as an exit ramp that splits from an ongoing roadway. Split lane traffic may sometimes create a bi-modality condition in which traffic in some of the lanes moves at a higher speed than traffic in other lanes. For example, the traffic in the lanes that are utilized to access an exit ramp may slow to a greater degree than the traffic in the other lanes that generally continue onward past the exit ramp. For example, at rush hour and other times during which the roadway carries an appreciable volume of traffic, the lane from which the exit ramp is accessed may be slowed to a much greater degree than the traffic in the other lanes that is generally continuing onward past the exit ramp. At other times, such as in instances in which the traffic volume is relatively light, all of the lanes of traffic for the road segment upstream of the diverging downstream road segments may proceed at approximately the same speed with little, if any, reduction of speed in the lane from which the exit ramp is accessed.
By identifying the bi-modality condition sometimes created by split lane traffic, the different speeds at which the split lane traffic is traveling along the road segment approaching the diverging downstream road segments may be identified and those different speeds may be associated with different lanes of the road segment. Thus, navigation systems may take into account the bi-modality condition of split lane traffic along a road segment approaching diverging downstream segments and, as such, provide enhanced navigation services, such as by directing a vehicle to a lane that is moving at a greater speed if the vehicle does not otherwise need to be in a lane that is moving at a slower speed, such as in an instance in which the route of the vehicle continues along the roadway such that the vehicle need not be in the lane with slower traffic that is accessing an exit ramp.
However, the impact of split lane traffic may vary from one junction to another as a result of, for example, the different traffic flow patterns supported by the junctions. Thus, the split lane traffic analysis may generate more accurate lane level traffic information for some junctions than for other junctions. Additionally, the determination of the bi-modality condition exhibited by split lane traffic is based upon the analysis of probe data, such as a compilation of probe points provided by vehicles traversing the road segment upstream of the diverging downstream road segments. The probe data is dynamic and varies from junction to junction and from time to time based on, for example, the number of probe points collected for respective road segments and/or the quality of the probe data, such as may be impacted by changes in the precision of the GPS that determines the location of the probe points. As a result of these variations in the probe data, the accuracy with which the bi-modality condition exhibited by split lane traffic along the road segment upstream of diverging downstream road segments may also vary, thereby impacting the accuracy of the lane level traffic information.